Behavior Effect of Hint Selection Penalties and Availability in an Intelligent Tutoring System

Proceedings of: Tenth International Confererence on Intelligent Tutoring Systems: Bridges to Learning (ITS 2010). Pittsburg, USA, June 14-18, 2010.his paper presents empirical results about the behavior effect of two different hinting strategies applied on exercises within an ITS: having some penalty on the scoring for viewing hints or not having any effect on the scoring; and hints directly available or only available as a result to an incorrect attempt. We analyze the students' behavior differences when these hinting techniques changed, taking into account the type and difficulty of the presented exercises.Work partially funded by the Learn3 project TIN2008-05163/TSI within the Spanish “Plan Nacional de I+D+I”, and the Madrid regional community project eMadrid S2009/TIC-1650.Publicad

Participatory design to lower the threshold for intelligent support authoring

One of the fundamental aims of authoring tools is to provide teachers with opportunities to configure, modify and generally appropriate the content and pedagogical strategies of intelligent systems. Despite some progress in the field, there is still a need for tools that have low thresholds in terms of the users’ technical expertise. Here, we demonstrate that designing systems with lower entry barrier can potentially be achieved through co-design activities with non-programmers and carefully observing novices. Following an iterative participatory co-design cycle with teachers who have little or no programming expertise, we reflect on their proposed enhancements. Our investigations focus on Authelo, an authoring tool that has been designed primarily for Exploratory Learning Objects, but we conclude the paper by providing transferable lessons, particularly the strong preference for visual interfaces and high-level pedagogical predicates for authoring analysis and feedback rules

Up and down the number line: modelling collaboration in contrasting school and home environments

This paper is concerned with user modelling issues such as adaptive educational environments, adaptive information retrieval, and support for collaboration. The HomeWork project is examining the use of learner modelling strategies within both school and home environments for young children aged 5 – 7 years. The learning experience within the home context can vary considerably from school especially for very young learners, and this project focuses on the use of modelling which can take into account the informality and potentially contrasting learning styles experienced within the home and school

Towards the Prediction of User Actions on Exercises with Hints Based on Survey Results

Proceedings of: 6th European Conference of Technology Enhanced Learning, EC-TEL 2011, Palermo, Italy, September 20-23, 2011.The actions a user performs on exercises depending on the different hinting techniques applied, can be used to adapt future exercises. In this paper, we propose a survey for users in order to know their different actions depending on different conditions. The analysis of preliminary results for some questions of the model shows that there is a correlation between some survey questions and the real student actions, but there is a case in which there is not such correlation. For the cases where that correlation exists, this correlation leads to think that some prediction of users actions based on survey results is possible.Work partially funded by the Learn3 project TIN2008-05163/TSI within the Spanish “Plan Nacional de I+D+I”, and the Madrid regional community project eMadrid S2009/TIC-1650

Analyzing collaborative learning processes automatically

In this article we describe the emerging area of text classification research focused on the problem of collaborative learning process analysis both from a broad perspective and more specifically in terms of a publicly available tool set called TagHelper tools. Analyzing the variety of pedagogically valuable facets of learners’ interactions is a time consuming and effortful process. Improving automated analyses of such highly valued processes of collaborative learning by adapting and applying recent text classification technologies would make it a less arduous task to obtain insights from corpus data. This endeavor also holds the potential for enabling substantially improved on-line instruction both by providing teachers and facilitators with reports about the groups they are moderating and by triggering context sensitive collaborative learning support on an as-needed basis. In this article, we report on an interdisciplinary research project, which has been investigating the effectiveness of applying text classification technology to a large CSCL corpus that has been analyzed by human coders using a theory-based multidimensional coding scheme. We report promising results and include an in-depth discussion of important issues such as reliability, validity, and efficiency that should be considered when deciding on the appropriateness of adopting a new technology such as TagHelper tools. One major technical contribution of this work is a demonstration that an important piece of the work towards making text classification technology effective for this purpose is designing and building linguistic pattern detectors, otherwise known as features, that can be extracted reliably from texts and that have high predictive power for the categories of discourse actions that the CSCL community is interested in

A serious game to improve engagement with web accessibility guidelines

This is an Accepted Manuscript of an article published by Taylor & Francis in Behaviour & Information Technology on 07 Jan 2020, available online: https://www.tandfonline.com/doi/full/10.1080/0144929X.2019.171145